Seismic waves generated artificially have been used for more than 50 years to perform imaging of geological layers. During seismic exploration operations, vibrator equipment (also known as a “source”) generates a seismic signal that propagates in the form of a wave that is reflected at interfaces of geological layers. These reflected waves are received by geophones, or more generally receivers, which convert the displacement of the ground resulting from the propagation of the waves into an electrical signal which is recorded. Analysis of the arrival times and amplitudes of these waves make it possible to construct a representation of the geological layers on which the waves are reflected.
FIG. 1 depicts schematically a system 100 for transmitting and receiving seismic waves intended for seismic exploration in a marine environment. System 100 comprises a source 118 on a streamer or cable 116a, pulled from ship or boat 102, on the surface 106 of ocean 108 (or other water mass, such as a large lake or river). Source 118 is operable to generate a seismic signal. System 100 further includes a set of receivers 120 (e.g., hydrophones) for receiving a seismic signal and converting it into an electrical signal, also located on streamer 116b, and marine seismic data recording/processing system 126 for recording and processing the electrical signals generated by receivers 120. Streamers 116 can also include birds 122 for guiding and maintaining position of streamers 116. Source 118, receivers 120 can be intermixed on one or more streamers 116, in any order. FIG. 1 depicts source 118 as a single source but it should be understood that the source may be composed of several sources, as is well known to persons skilled in the art. Also part of system 100 are antennas 124 that can be used to transmit information and controls between ships 102, land bases, birds 122 (some birds 122 can also include antennas 122) and other devices.
In operation, source 118 is operated so as to generate a seismic signal. This signal propagates through water 108, in the form of transmitted waves 124 that generate reflected waves 126 when they reach an interface 110 between two layers 108 (ocean) and 112 (a geological layer, in this case, the ocean floor; it can also be appreciated by those of skill in the art that sometimes the transmitted waves 124 travel upwards instead of downwards, and when they reach the interface between atmosphere/air 104 and ocean 108 (i.e., at ocean surface 108) downward reflected waves 126 can also be generated (not shown); these are known by those of skill in the art as “ghosts”). Each receiver 120 receives one or more reflected waves 126 and converts them into an electrical signal. System 100 intends to image the subsurface regions 112 to determine the presence, or not, of hydrocarbon deposit 114.
FIG. 2 depicts schematically a system 200 for transmitting and receiving seismic waves intended for seismic exploration in a land environment. System 200 comprises a source 202 consisting of a vibrator operable to generate a seismic signal, a set of receivers 204 (e.g., geophones) for receiving a seismic signal and converting it into an electrical signal and land seismic data recording/processing system 206 for recording and processing the electrical signals generated by receivers 204. System 200 can further include antennas 124 for communications between vehicles 224a, 224b, receivers 204, and land seismic data recording/processing system 206.
Source 202, receivers 204 and land seismic data recording/processing system 206 (located on vehicle 224b) are positioned on the surface of ground 208. FIG. 2 depicts source 202 as a single vibrator but it should be understood that the source may be composed of several vibrators, as is well known to persons skilled in the art. In operation, source 202 is operated so as to generate a seismic signal. This signal propagates firstly on the surface of the ground, in the form of surface waves 210, and secondly in the subsoil, in the form of transmitted waves 212 that generate reflected waves 214 when they reach an interface 220 between two geological layers. Each receiver 204 receives both surface wave 210 and reflected wave(s) 214 and converts them into an electrical signal, which signal thus includes a component associated with reflected wave 214 and another component associated with surface wave 210. Since system 200 intends to image the subsurface regions 216 and 218, including hydrocarbon deposit 222, the component in the electrical signal associated with surface wave 210 is undesirable and should be filtered out.
Velocity models are key components of seismic imaging, and consequently, to reservoir description and geo-mechanical analysis. As its name implies, a velocity model is a visual representation of the velocity of sound waves in different locations underground. Note that “underground” can mean in land-based areas, for example, within the continental United States, or underground under the ocean floor (but can also include the different velocities of the sound as it passes through different ocean water layers). Thus, as shown in FIG. 3, first transmitted seismic wave 304 can have many different velocities as it travels from source 118, through different water layers 302a-d, through different underground layers 112a-c, and is finally reflected and received by receivers (not shown in FIG. 3). As those of ordinary skill in the art can appreciate, in standard sea water conditions, the first velocity is in the order of about 1,500 meters-per-second (mps). FIG. 3, a greatly oversimplified view of a velocity model for a fictitious area, shows up to seven different velocity-constant layers, all of which are relatively flat. This generally is not the case. For example, in an actual thrust belt, which is a geological formation caused by compressional tectonics, a natural process that ultimately results in the formation of large mountain ranges, the layers would generally not be flat, instead, would be undulating, wave-like in appearance, and even exhibit abrupt “cliff” or vertical separations and other manners of discontinuities. As those of ordinary skill in the art can appreciate, thrust belts present both significant financial rewards as well as financial risk: significant oil and gas deposits can be found around thrust belts, but, not every thrust belt will exhibit the properties of oil and gas deposits, and so “bust” drillings can occur, at the cost of about ten million dollars or so per drilling.
If the sub-strata were more or less homogenous, the velocity model would be relatively easy to create (as shown, for example, in FIG. 3); however, it is known that there are many different geological factors that will make it very difficult to create accurate depictions of the velocity model. For example, some sub-surface areas have significant complex features such as strong velocity or anisotropic parameter variations or complex geological formations such as salt and basalt structures, heavily faulted zones, anisotropic environments due to sedimentation or fracturing (an anisotropic environment is one in which seismic waves move at higher or lower velocities depending upon whether they move in directions along or across rock bed layers), over-thrusts, shallow gas, among others. The processing of the reflected and refracted sound waves, therefore, can become extremely complicated.
Those of ordinary skill in the art can appreciate that velocity can vary depending upon such things as lithology (the type of rock), and depth of burial, since rocks under pressure tend to have higher velocity (due, in part, to increasing density). When imaging velocity models following processing of received seismic waves, it is common to use colors, or shading, to represent a rainbow scale of rock velocity. Thus, similarly colored areas exhibit similar velocities. According to one non-limiting example, a first color or colors—purples and/or blues—represent the lower velocities in the range of 3,000 to 3,500 meters per second. A third set of colors—reds, yellows and oranges—represent velocities that are about 6,000 meters per second. A second set of colors, for example green, represents velocities that are in the range of about 4,000-5,000 meters per second. As discussed above, seismic data is obtained by generating sound waves, and locating receivers, usually a large number of them (in the order of several hundred to several thousand depending on the location and the expected underground geological topology), to collect the data.
Inversion processes, or more formally known as the field of inverse theory, as known to those of skill in the art, deals with the mathematics of describing an object based on measurements or observations that are associated with that object. For example, knowing what signals enters a black box, and knowing the signals that exit it, one might be able to discern, for that input alone, what type of processing occurs within the black box. In the world of seismic study, tomography is a specific type of inversion process. A formal description of this process was given by Backus and Gilbert (1968) in the context of inverse theory applied to geophysical observations. In most real-world situations, however, there is never a sufficient amount of observed data to determine a unique solution, and the data that is available may be noisy and/or unreliable. In the case of travel time measurements made in a surface seismic experiment, there exists the specific inverse problem of trying to determine the velocity structure of the earth.
In regard to tomography and the context of seismic imaging and velocity model building, construction of an estimate of the subsurface velocity distribution occurs based on a series of measurements of travel times or amplitudes associated with seismic reflections, transmissions, and/or refractions, perhaps including some geological constraints. This includes information determined prior to migration (in the data domain) and also after completion of a migration in the migrated (image) domain. Within each of these domains, there is arrival time or depth (kinematic) information as well as amplitude and wavelet (dynamic) information. Therefore, there are at least four basic classes of observables we could use to solve the tomographic inverse problem. To simplify the procedure, travel time information alone can be used, or migrated depth information alone, or, more completely, the measured amplitudes of the waveforms of the recorded data including the associated arrival times and wavelets can be used.
Tomography based on ray tracing can be formulated for reflection, transmission, and refraction. Several techniques for computing statics corrections in seismic reflection surveys make use of refraction tomography, whilst transmission tomography is used for cross-well applications where both the source and the receiver are inside the medium (within boreholes, for example) and also for velocity seismic profiling (VSP) walk-away studies. A vertical seismic profile is a technique of seismic measurements generally used for correlation with surface seismic data. Generally speaking, the defining characteristic of a VSP is that either the energy source, or the detectors, or sometimes both, are in a borehole. As a result, there is access to, and can be made use of, transmitted arrival information. Exploiting amplitude information in addition to arrival times can further assist ray-based tomography in estimating a reliable velocity model. In addition to velocity estimation, tomography can be used to estimate other earth parameters, such as absorption.
Accordingly, full waveform inversion (FWI) has been an important method to build velocity models for seismic imaging (see, Tarantola, A., 1984, Inversion of Seismic Reflection Data in the Acoustic Approximation: Geophysics,” 49, 1259-1266; and Sirgue, L., and R. G. Pratt, 2004, “Efficient Waveform Inversion and Imaging: A strategy for Selecting Temporal Frequencies,” Geophysics, 69, 231-248.; and Virieux, J., and S. Operto, 2009, “An Overview of Full Waveform Inversion in Exploration Geophysics,” Geophysics, 74(6), WCC127-WCC152, the entire contents of each of which are incorporated herein in their entirety). Classical FWI involves the minimization of a square misfit function between the calculated and observed data. Non-linear gradient based optimizations have also been used (see, Pratt, R., C. et al., 1998, “Gauss-Newton and Full Newton Methods in Frequency-Space Seismic Waveform Inversion,” Geophysical Journal, International, 13, p. 341-362; Ravaut, C. et al., 2004, “Multi-scale Imaging of Complex Structures from Multifold Wide-Aperture Seismic Data by Frequency-Domain Full Waveform Tomography: Application to a Thrust Belt,” Geophysical Journal, International, 159, 3, p. 1032-1056; Sirgue, L., and R. G. Pratt, 2004, “Efficient waveform inversion and imaging: A Strategy for Selecting Temporal Frequencies,” Geophysics, 69, 231-248; Choi et al., 2008; Ma and Hale, 2011) with complex strategies for making the results more linear (filtering, weighting, and muting of the data, among other data manipulations). These strategies mitigate non-linearity but cannot recover the features that are not covered by the intrinsic resolution of the method.
Velocity model building, therefore, is a significant step in seismic depth imaging for both land and marine seismic imaging. As those of ordinary skill in the art can appreciate, in order to provide a representative image of the geographical area of interest (GAI), i.e., in order to properly interpret the seismic waves to provide accurate seismic images, it is necessary to have a well-defined velocity model of the general area. However, compared to conventional velocity model building methods based on picking (see, Stork, C., 1992, “Reflection Tomography in the Post-Migrated Domain,” Geophysics, 57, 5, 680-692; Liu, Z., 1997, “An Analytical Approach to Migration Velocity Analysis,” Geophysics, 62, 4, 1238-1249; Woodward, M., et al., 1998, “Automated 3D Tomographic Velocity Analysis of Residual Moveout in Prestack Depth Migrated Common Image Point Gathers,” SEG, Expanded Abstracts, 17, 1, 1218-1221; Guillaume, P., et al., 2001, “3D Finite-Offset Tomographic Inversion of CRP-Scan Data, With or Without Anisotropy,” SEG, Expanded Abstracts, 20, no. 1, 718-721; Woodward, M., et al., 2008, “A Decade of Tomography,” Geophysics, 73, 5, VE5-VE11; Guillaume, P., et al., 2008, “Kinematic Invariants: An Efficient and Flexible Approach for Velocity Model Building,” SEG, Expanded Abstracts, 27, no. 1, 3687-3692), full wave form inversion (FWI) (see, Virieux, J., et al., 2009, “An Overview of Full Waveform Inversion in Exploration Geophysics,” Geophysics, 64, WCC1-WCC26) is appreciated for providing high resolution and structurally conformable velocity models (i.e., a velocity model that accurately conforms with, or resembles, the actual structure of the layers below ground). The resulting velocity models are, however, generally only trustworthy for the high resolution velocity structures of the near surface investigated by diving waves.
Thus, there are certain problems with determining accurate velocity models using current methods and system, especially when the velocity models are developed for areas other than near surface, and especially when using anything other than full wave form inversion. Accordingly, it would be desirable to provide methods, modes and systems for using a ray based tomography process to develop enhanced velocity models for geographical areas of interest.